Geolocation is a term that describes a broad range of technologies for deriving the spatial location (e.g., X, Y, Z Cartesian coordinates) of an object by processing transmitted signals that are received, emitted, or reflected by that object. While in selected embodiments described in this document and illustrated in the attached drawings the transmitted signals are radio frequency (RF) signals, geolocation and selected principles described here may be extended to other transmitted signals, including sound/ultrasound signals.
Known geolocation examples include the Global Positioning Satellite (GPS) systems and cell phone networks, but other RF geolocation systems may be used in areas as diverse as inventory management, asset tracking, law enforcement, and the military. There are several different modes of operation of these systems. For example, the GPS systems attempt to enable an object to geolocate its own position by reading RF signals emitted by multiple satellites. The RF signals contain precise information about the location of the satellites and the time of emission of the signals. The object can acquire the signals from the multiple satellites, read the data contained in the signals, use standard multilateration techniques to calculate the coordinates of the object's position relative to the satellites, and project the coordinates onto pre-defined references, such as maps. (Multilateration techniques are based on the measurement of the difference in distance from the located object to two or more stations at known locations that broadcast at known times.) For example, the coordinates may be used by a vehicle's software to indicate the position of the vehicle on a map, and to map a path to another set of coordinates.
Cellular telephone systems may also perform geolocation. In this case, however, a cell phone can geolocate its position by using data acquired from cell towers in a manner similar to that used by the GPS systems. In the cell systems, the technique can also be used in reverse, where the cell network geolocates the cell phone using signals received by multiple cell towers from the cell phone. This technique is often used by law enforcement to track individuals.
Similar techniques can be used in inventory management where radio frequency identifier (RFID) tags can emit signals which can be, e.g., triangulated by antenna arrays placed around warehouses or in locations like docks and shipping holds.
In the above-described cases, the geolocation may be achieved by a combination of geometrical calculations, such as triangulation, trilateration, or multilateration and acquiring critical transmission data by reading key information embedded in the signals by the transmission source or some other part of the system. For example, the GPS system embeds in the signal highly precise information about the X, Y, Z coordinates of the satellites and the signal emission times (ephemeris data). If this data can be read on a precise receiver that has the same time reference as the satellite time reference, the distances from the receiver to the satellites can be calculated. The receiver's location can then be determined through trilateration.
It is more problematic to geolocate through derivation of the critical spatial parameters of a source without being able to read the information content of the source's signal. The process of geolocation based on the ability to detect the signal at the physical layer is more general and does not necessarily require receivers with special properties or a functioning sophisticated infrastructure like the GPS systems or the cellular telephone systems.
Techniques that perform geolocation based on the physical layer detection of the signals generally attempt to look at one or more properties of the signal, and measure how these properties change as function(s) of some spatial variable(s). A large dish antenna, for example, can be rotated until the received signal is maximized in a particular direction. This provides direction of arrival (DoA) information. If the result from one antenna is compared with similar results taken from additional, spatially diverse antennas/locations, triangulation may reveal the apparent source of the signal. Similarly, using the time difference of arrival (TDoA) of signals between or among multiple antennas at different known locations, the antenna array can be employed to geolocate a source by using the time of arrival to estimate the sides of the triangles rather than the angles, and perform trilateration as opposed to triangulation. Analogous techniques can be used by employing other signal properties, such as detected signal strength (DSS).
In general, it is necessary to observe the signals from more than one location and to compare the results obtained at the different locations. In practice this may be done by placing different antennas at the various locations. It may also be done by moving a single antenna to the different locations and comparing sequential measurements. Either the receiver or the transmitter, or both end points can be moving or stationary, and the mobility may take place independent of the geolocation process or be part of the geolocation process. In other words, the mobility may be used as part of the geolocation process to search for the source, or it may result from moving objects attempting to geolocate themselves in order to determine their location and/or trajectory. The former mobility may enhance the accuracy of geolocation, the latter may degrade geolocation accuracy by placing strict time limits on how rapidly the process must be performed. This may eliminate the ability to use more computationally complex methodologies.
Spatial correlation and spatial diversity are generally the principles underlying such techniques. Spatial correlation refers to the concept that if the properties of a source which is emitting a signal are known, as are the details of the environment through which the signal is propagating, the field of the signal is fully determined (defined) at all points in space.
Spatial diversity, in the context of geolocation, usually refers to the ability to measure properties of the field at different points in space and from these to determine the degree of spatial correlation of the field. Spatial correlation refers to the ability to predict certain properties of a signal emitted into a known spatial environment at various locations in the environment. To illustrate spatial diversity (as the concept applies to geolocation), comparing measurements of signal properties taken at multiple points in space in a highly spatially correlated field can be used to calculate the location of the source of the signal. In general, if a source emits a signal, and the signal at a sufficient number of points in space is measured (adequate spatial diversity), then if the signal is spatially well-correlated, the location of the source may be inferred from the inherent structure of the field.
In reality, all fields are spatially correlated since propagation of EM waves is fully deterministic. Since an observer in practice may not know the specific details of the environment through which a signal propagates, however, then spatial correlation becomes a measure of the observer's knowledge of the environment and computational ability to predict the field. Hence, if the environment is unknown, the spatial correlation degrades and becomes significantly less than perfect and the observer loses the ability to deduce the location of the source by making spatially diverse measurements of the field.
If either of these properties (spatial correlation and spatial diversity) is degraded, the accuracy of the geolocation may suffer and in some cases geolocation may become impossible with conventional techniques. Spatial correlation is primarily degraded when there are unknown elements in the propagation environment that corrupt the signal, such as multipath scattering and structures that attenuate the signal or cause dispersion. A particularly serious degradation may occur when there is no LoS signal to the observer locations. In that case, the signal may only reach the observer by following a multipath scattering route and hence the processes that use triangulation or multilateration generally fail to provide an acceptable position estimate. Spatial diversity is usually degraded by using too few antenna locations or by having the diverse locations too close together to resolve the signal differences. This can result in the failure of the geolocation process.
Noise, interference, and poor measurement techniques may also degrade the received signal and reduce the quality of geolocation. When these problems create a reduction of the accuracy of the geolocation, but the source location remains at some statistical center, we refer to a degradation of “accuracy.” If this degradation of accuracy is caused by measurement noise whose statistical properties are known, then it may be possible to use statistical estimation theory to recover the mean location of the signal and improve the accuracy. This may be equivalent, for example, to providing an observer with many measurement results spread over a large area, and informing the observer that the results follow a Gaussian (or other known) distribution. The observer can then estimate the true location to be at the center of the Gaussian peak, resulting in a highly accurate geolocation, even though the results may be widely spread out. In reality, the statistics may not be known sufficiently well, and so the accuracy error can be reduced only to the Cramer-Rao limit known from the statistical estimation theory. The magnitude of accuracy errors based on noise typically scales with the actual distance between the source and the observer.
When there is no detectable LoS signal, the statistical estimation technique often appears to reduce the effect of the accuracy errors such as measurement noise, but the final solution may be at the wrong location, often very far from the correct location. In practice, the solution often geolocates the strongest LoS scatterer in the field, instead of the original transmission source. This is a serious form of error, called a bias error, and it may occur when one attempts to perform triangulation or multilateration without having at least a weak (but detectable) LoS signal to provide spatial correlation. Consequently, conventional state-of-the-art systems apply many sophisticated techniques to ensure that effects like multipath scattering do not degrade the ability to recover even weak LoS signal components, or that they use the NLoS components to infer the LoS.
Hence, although some examples in the scientific literature refer to NLoS geolocation, they generally do not literally mean geolocating in perfect NLoS conditions, i.e., without a detectable LoS signal. Instead, they typically mean recovering weak LoS signals that are swamped with multipath (NLoS signals) or using a-priori knowledge of the geometrical obstacles that are blocking the signal to infer the actual LoS path, or estimating the maximum error of the location by placing bounds on how far the hidden LoS component can deviate from the visible NLoS signal. These techniques may not work well for deeply hidden sources in what is referred to as multi-hop or “true” NLoS conditions.
The conventional technique used to obtain geolocation information in severe multi-hop NLoS cases is to use a mobile observer who can follow the signal round the corners. This is similar to how a person can locate misplaced objects, such as car keys or a wallet, by activating a small acoustic beeper attached to the objects and following the sound until they are found. Such techniques, however, are not generally applicable, have serious security and safety limitations, and are not physically possible in many circumstances.
Finally, there are variations in how the signals required to geolocate an object are created. In some cases the object itself may be emitting the RF signal. For example, the military authorities are interested in the ability to geolocate insurgents activating roadside bombs with cell phones. Other cases, such as GPS system applications, include multiple satellites emitting signals, while the object to be geolocated is passively observing the signals. In other cases, an observer may actively “ping” the environment, attempting to observe reflections from an object of interest and geolocate the object. Still other techniques may use an independent beacon to illuminate a target and attempt geolocation by observing reflections from the target. Other approaches are possible.
In general, the various applications of geolocation include the following:
Using a passive spatially diverse array to geolocate an active source;
Using an active spatially diverse array to geolocate a passive source;
Performing self-geolocation by observing the spatially diverse emissions of an active array;
Performing self-geolocation by using a passive array to detect signals emitted by an active source (active beacon); and
Performing self-geolocation using an active array to reflect signals from a passive source reflector (a passive beacon).
Needs in the art exist for better geolocation techniques, including techniques capable of true NLoS geolocation.